Enterprise data is generated at a high speed mostly through transactional systems used by the companies. Organizations can gain business value by exploring and analyzing transactional data, which may be generated within the enterprise or other raw data from internal or external sources (e.g. social media). Business entities may utilize database offering to store big data. Data has no meaning if it is only stored and not analyzed. Analysis and searching over stored data may be accomplished by manual identification of the data structures of the database and the underlying backend system. On-the-fly analysis of data stored inside a company database helps business entities achieve a better insight on the stored data and makes future decision faster and more informed. Some search tools replicate the data present in a database into a search index and then perform analysis and search operations on the search index. Processing the data may be performed through a thick middle layer between the database and the search tool. This processing may also include data transfer processes, search index updates, replication of data, etc. The introduction of “in-memory” technology has reduced the time and cost of data processing. According to one embodiment, “in-memory” technology allows working with data stored in random access memory (RAM) for processing without the traditional data retrieval from the database system.